Results 161 to 170 of about 6,391,262 (321)

SPINEX-symbolic regression: similarity-based symbolic regression with explainable neighbors exploration

The Journal of Supercomputing
Abstract This article introduces a new symbolic regression algorithm based on the SPINEX (similarity-based predictions with explainable neighbors exploration) family. This new algorithm (SPINEX_SymbolicRegression) adopts a similarity-based approach to identifying high-merit expressions that satisfy accuracy- and structural similarity metrics.
Mohannad Z. Naser, Ahmad Z. Naser
openaire   +2 more sources

Symbolic Time Series Analysis in Economics [PDF]

In this paper I describe and apply the methods of Symbolic Time Series Analysis (STSA) to an experimental framework. The idea behind Symbolic Time Series Analysis is simple: the values of a given time series data are transformed into a finite set of ...
Juan Gabriel Brida
core  

Liver Endothelia Orchestrate MASH‐Associated Macrophage Zonation Through FSTL1‐ITGA4 Axis

Advanced Science, EarlyView.
Liver inflammation in MASH fundamentally hinges on the newly defined Kit/STAT2/FSTL1/ITGA4 axis. Declining endothelial Kit collapses normal hepatic zonation, driving an aberrant FSTL1 gradient that recruits pathogenic macrophages. Strikingly, targeting FSTL1‐ITGA4 with anti‐VLA4 restores spatial immune homeostasis and halts disease progression ...
Lin Sun, Zhensheng Yue, Zhiqiang Fang, Hao Xu, Wei Du, Yuwei Ling, Jingjing Liu, Ping Song, Fei He, Juanli Duan, Lin Wang   +10 more
wiley   +1 more source

Computing framework for symbolic regression

U današnjem "data-driven" društvu eksponencijalni rast podataka zahtijeva učinkovite alate za analizu i interpretaciju istih. Simbolička regresija, metoda za otkrivanje matematičkih izraza koji opisuju složene uzorke podataka bez unaprijed definiranih ...
Ivančević, Josip
core   +2 more sources

A Generative Neuro‐Symbolic AI for Protein Sequence Design

Advanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne, Delphine Dessaux, Samuel Buchet, Lucie Barthe, Liza Ammar‐Khodja, Bessam Azizi, Valentin Durante, Gianluca Cioci, Simon de Givry, Alain Roussel, Luis F. Garcia‐Alles, Thomas Schiex, Sophie Barbe   +12 more
wiley   +1 more source

Physically interpretable interatomic potentials via symbolic regression and reinforcement learning

npj Computational Materials
The development of next-generation molecular simulation models requires moving beyond predefined functional forms toward machine learning (ML) techniques that directly capture multiscale physics.
Bilvin Varughese, Troy D. Loeffler, Suvo Banik, Aditya Koneru, Sukriti Manna, Karthik Balasubramanian, Rohit Batra, Mathew J. Cherukara, Orcun Yildiz, Tom Peterka, Bobby G. Sumpter, Subramanian K.R.S. Sankaranarayanan   +11 more
doaj   +1 more source

Label‐Free Myelin Fingerprinting: An Adult Human Post‐Mortem Brain Slice Platform via Coherent Anti‐Stokes Raman Spectroscopy

Advanced Science, EarlyView.
A serum‐free, air–liquid interface organotypic slice culture model preserves human post‐mortem corpus callosum tissue, successfully recovering from slicing trauma to reflect the donor's underlying disease state. Pairing label‐free Coherent anti‐Stokes Raman scattering (CARS) microscopy with k‐means clustering enables objective, high‐resolution ...
Kasra Roya‐Kouchaki, Jeroen P. Korterik, Femke Tjebbes, Geert J. Schenk, Herman L. Offerhaus, Antonio Luchicchi   +5 more
wiley   +1 more source

A Closed‐Loop Framework for Inverse Design: Dynamic Training and Intelligent Optimization for Heterostructured Materials

Advanced Science, EarlyView.
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong, Xueru Zheng, Xiao Zhou, Zhengheng Tao, Wan Han, Jingyi Pan, Dian Wu, Ning Gao, Lei Liu, Zhongyang Wang, Fanchao Meng, Tongxiang Fan   +11 more
wiley   +1 more source

Extended Anionic Network in Mixed‐Valent Nitridocobaltates(I/II) LnCo2N2 (Ln = La, Pr, Nd)

Advanced Science, EarlyView.
This study presents the high‐pressure synthesis of LnCo2N2 (Ln = La, Pr, Nd) with Co in mixed valent states of +I/+II. The compounds demonstrate the stabilization of a nitridocobaltate with extended anionic Co–N layers where Co is threefold coordinated.
Nina A. M. Prinz, Jonas M. Albrecht, Dominik Werhahn, Simon Steinberg, Clemens Ritter, Simon D. Kloß   +5 more
wiley   +1 more source

Large‐scale Whole‐Exome Sequencing Defines the Protein‐Coding Architecture of Retinal Structure, Visual Function, and Major Blinding Diseases

Advanced Science, EarlyView.
Large‐scale whole‐exome sequencing in 356,982 UK Biobank participants defines the protein‐coding architecture of retinal structure, visual function, and major blinding diseases. Pleiotropic genes, including CFI, C3, and RIOX1, bridge multiple retinal phenotypes, while experimental validation of FYB2 implicates RPE barrier dysfunction, providing ...
Jianqing Li, Yijun Ge, Jingxiao Du, Liu Yang, Bangsheng Wu, Chenyue Hang, Mengxi Shen, Yimin Mao, Ting Zhang, Qiyu Bo, Tianyuan Zhao, Yutian Jiao, Yazhi Wang, Shunxiang Gao, Jieqiong Chen, Junran Sun, Tong Li, Huixun Jia, Yang Dou, Wei Cheng, Xiaoling Wan, Jintai Yu, Xiaodong Sun, Bai Lu   +23 more
wiley   +1 more source